New Prism ISP software from Teledyne FLIR delivers advanced Signal Processing and Expands AI at the Edge

prism ISP

Teledyne FLIR has announced version 1.0 of its Prism ISP, a highly optimized image signal processing software development kit (SDK) for embedded systems designed to maximize performance in thermal and multispectral applications.

Designed to run on low-power GPUs from Qualcomm and NVIDIA, Prism software includes image-enhancing functionality for:

  • Noise reduction
  • Super-resolution
  • Electronic image stabilization
  • Infrared (IR) and electro-optical (EO) video fusion
  • Turbulence mitigation
  • Locally adaptive tone mapping
  • Super Resolution – Prism ISP.png

The Prism ISP libraries enable integrators in the defense, commercial, and industrial markets to dramatically enhance imaging quality as part of artificial intelligence (AI) data capture at the edge, improving performance, lowering development costs, and shortening time to market. Developers, data scientists, and perception engineers can utilize Prism ISP with Teledyne FLIR market-leading thermal cores, including Boson®, Tau® 2, Hadron™, and Neutrino™®.

In addition to Prism ISP, Teledyne FLIR has also enhanced Prism AI, the company says. This powerful, efficient perception software enables classification, object detection, and object tracking in thermal and visible light spectrums. The AI element now provides additional high-performance models trained on the world’s largest application-specific thermal image datasets, including ground intelligence, surveillance, and reconnaissance (ISR), air-to-ground, and counter-drone applications, complementing the automotive software library announced last year.

“Prism ISP is critical to thermal-based AI system development, offering an unprecedented performance while reducing development costs,” said Dan Walker, vice president, product management, Teledyne FLIR. “Within our end-to-end, computational imaging ecosystem featuring Prism AI, Teledyne FLIR can now support a wider array of projects and custom development that utilize low-power, embedded processors at the edge.”

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